Multi-objective Optimisation of Composite Laminates under Heat and Moisture Effects using a Hybrid Neuro-GA Algorithm

Authors: M. R. Ghasemi, A. Ehsani

Abstract:

In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.

Keywords: Composite Laminates, GA, Multi-objectiveOptimisation, Neural Networks, RBFNN.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1072902

References:

[1] Jones, R.M., ''Mechanics of Composite Materials'', McGRAW-HILL international student edition, Washington D.C, 1975.
[2] Rao, S.S. "Optimization Theory and Applications", Wiley Eastern Ltd, 1991.
[3] Ghasemi, M.R., "Structural optimization of trusses and axisymmetric shells using gradient based methods and genetic algorithms", Department of civil eng. University of Wales Swansea, November 1996.
[4] Ghasemi M.R. and Ghasemi, M., "Software Development for Prediction of Buckling Analysis and Optimisation of Tapered Gabled Frames Using Neural Networks", Proceeding of 5th ASMO/ISSMO Congress, UK 2004.
[5] Soremkeun,A.E, "Genetic Algorithm for composite laminates design and optimisation", Virginia Polytechnic Institute and state University, 1997.
[6] Adeli, H., "Neural Networks in Civil Engineering", 1989-2000. J. Computer-Aided Civil and Infrastructure Engineering, 16, 126-142, 2001.
[7] Wasserman, P.D., "Advanced Method in Neural Computing", USA, Prentice Hall Company, Van Nostrand Reinhold, New York, 1993.
[8] Muller B. and Reinhardt J. Neural Networks. Spring Verlag.1990, Berlin.
[9] MATLAB MANUAL, The Math Works Inc., 2002 Matlab help.